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Machine Learning Startup Jobs in Washington, DC (NOW HIRING)

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Is resourceful, proactive, and comfortable operating in a fast-moving startup environment. * Is ...

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Is resourceful, proactive, and comfortable operating in a fast-moving startup environment. * Is ...

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Is resourceful, proactive, and comfortable operating in a fast-moving startup environment. * Is ...

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company ... Operates with a startup mentality focused on technical depth, creative problem-solving, and ...

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company ... Operates with a startup mentality focused on technical depth, creative problem-solving, and ...

Ability to excel in a fast-paced, startup-like environment * Knowledge of developer tooling across the software development life cycle (task management, source code, building, deployment, operations ...

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Showing results 1-20

Machine Learning Startup information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do machine learning startup jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning startup in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Startup position, and why are they important?

To succeed in a Machine Learning Startup, a strong background in computer science, statistics, and applied mathematics is essential, along with practical experience building and deploying machine learning models. Proficiency in tools such as Python, TensorFlow, PyTorch, and cloud-based platforms, as well as familiarity with data versioning and model deployment systems, is highly valuable. Adaptability, entrepreneurial thinking, and strong communication skills are crucial for thriving in the dynamic startup environment. These competencies enable effective product development, rapid iteration, and impactful collaboration within a fast-paced, resource-constrained setting.

What are the typical responsibilities and daily challenges when working at a Machine Learning Startup?

At a Machine Learning Startup, your daily tasks often include collecting and preprocessing data, training and validating models, collaborating with engineers to deploy solutions, and iterating rapidly based on feedback and performance metrics. You may also contribute to brainstorming sessions, product roadmapping, and customer discovery processes. Common challenges include working with limited labeled data, balancing research with production needs, and managing shifting priorities as the business pivots or scales. This dynamic environment provides a valuable opportunity to make a tangible impact, develop a broad skill set, and gain exposure to multiple aspects of both technology and entrepreneurship.

What is a Machine Learning Startup job?

A Machine Learning Startup job typically involves working in a fast-paced, early-stage company focused on developing and applying machine learning technologies. Employees may take on diverse responsibilities, including data collection, model development, algorithm optimization, and deployment. Since startups require adaptability, roles often blend research, engineering, and business-oriented problem-solving. These positions offer opportunities to work on cutting-edge innovations but may also demand long hours and rapid prototyping.

What are the most commonly searched types of Machine Learning Startup jobs in Washington, DC? The most popular types of Machine Learning Startup jobs in Washington, DC are:
What are popular job titles related to Machine Learning Startup jobs in Washington, DC? For Machine Learning Startup jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Startup jobs in Washington, DC look for? The top searched job categories for Machine Learning Startup jobs in Washington, DC are:

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted 21 hours ago


Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.